A software-defined radio (SDR) application for monitoring and logging radio frequency interference in amateur radio bands, based on GNU Radio.

Both QRM, “Are you being interfered with?” and QRN, “Are the atmospherics strong?” are still common abbreviations used in Amateur Radio. Today, QRM stands for human-made noise, as opposed to QRN, which indicates noise from natural sources. If you hear an operator say, “I’m getting some QRM,” it means there’s man-made interference affecting your transmission. **

Periodic broadband QRM that appears at random times is particularly challenging to identify and locate, especially on the shortwave bands. Sometimes it helps to determine the timing of the QRM to infer its source.

This tool lets you record the spectrum (either manually or at periodic intervals) and create image grids for easy analysis. It also generates RMS CSV files for further analysis.

• Optimized for Raspberry Pi (Linux); also works on Windows and macOS
• SDR support out of the box: RTL‑SDR v4 and SDRplay RSP1A (requires a 3rd‑party driver compilation step)
• Python 3.10+; requires conda/mamba with the conda‑forge channel.

Architecture:

• Backend: Python application using GNU Radio for SDR processing
• Frontend: Alpine.js single-page application served by the Python backend
• Dependencies: All frontend dependencies are included via CDN - no npm/node required
• Installation: Simply install the conda environment and run python main.py

For a detailed application description, usage instructions and screenshots check my web page:

qrm-logger is ready to run after installing the conda environment - no build step required.

System Requirements:

• Python: 3.10 or higher (conda required)
• Operating System: Windows, Linux, macOS
• SDR Hardware: RTL-SDR v4 (or GNU Radio compatible devices)

git clone https://github.com/do1zl/qrm-logger
cd qrm-logger

Alternative: If you don't want to install git - go to the <> Code dropdown on top of this page and and choose 'Download ZIP'

You need a conda package manager like Miniforge or Miniconda in order to install the dependencies of the application. Miniforge is preferred because it uses conda-forge as the default channel. You can also try micromamba for a minimal install.

The regular python install from the App Store is not sufficient to run the application!

Windows:

• Install Miniforge. Recommended install settings: Install for "Just me". Default Location. Options: Check "Create start menu shortcuts". Uncheck "Add miniforge3 to path". Uncheck "Register Miniforge3 as my default Python".
• Open "Miniforge Prompt" from start menu. You will see a prompt prefix (base)

Linux:

• Install Miniforge
• The installer will ask whether to enable automatic shell activation. Recommendation: choose 'yes', then disable automatic base environment activation as suggested there. Also see here

Mac:

• Install miniconda or miniforge using brew, or use the download.
• See this brew. Make sure to run the described steps to initialize your shell. Also see here

A conda environment stores all the dependencies required for the application. Read more about conda here.

The following steps use mamba for the CLI commands. You can substitute this command with conda in case you are running miniconda. Mamba is a replacement conda package manager, both use the same command line syntax.

Important: You must execute these commands from a conda shell. A conda shell always displays a prompt prefix like (base). If you cannot see this prefix in your terminal, check 'Install conda package manager' section again.

# Important: You must execute these commands from a conda shell

# Go to the project directory
cd qrm-logger

# Create environment from environment.yml file
# This will create 'qrm-logger' environment and install all required packages 
mamba env create -f environment.yml

# or choose a different environment name (optional)
# mamba env create -f environment.yml -n qrm1

# Activate the environment. Your prompt prefix will change to (qrm-logger)
mamba activate qrm-logger

# Check installed packages (optional)
mamba list

# List existing environments (optional)
mamba env list

# Activate environment
mamba activate qrm-logger

# Start the application (web interface)
python main.py

# OR: Record once and exit (no web interface)
# python main.py --run-once

• Navigate to http://localhost:7060 in your web browser

The application can be adapted to all devices supported by GNU Radio. Currently, only RTL-SDR is supported out-of-the-box, but it should be easy to integrate other SDRs supported by GNU Radio.

See sdr_support.md for information on how to add support for other devices.

qrm-logger uses TOML files for user-editable configuration:

• config-static.toml - Static defaults (SDR, recording, visualization, web server)
• config-bandplan.toml - Amateur radio band definitions
• config-capture_sets.json - Frequency monitoring strategies
• config-dynamic.json - Runtime settings (managed via web interface)

All files are auto-generated on first run. Edit config-static.toml and config-bandplan.toml to customize your setup.

See configuration.md for detailed documentation.

By default, the web interface is configured for local access only (localhost:7060). This is the most secure option as it prevents network access from other devices.

To allow network access:

1. Edit config-static.toml
2. Change host = "localhost" to host = "0.0.0.0" in the [web] section
3. Restart the application

Warning: Only use 0.0.0.0 on trusted networks since there is no authentication.

For headless 24/7 monitoring on Raspberry Pi, qrm-logger includes pre-configured systemd service files for easy installation. See service_install.md

rms.md

output_files.md

configuration.md

troubleshooting.md

I am still pretty new to the world of SDR programming with gnu-radio. There might be potential to improve certain data handling & FFT calculations in the application.

• PySDR: A Guide to SDR and DSP using Python (pysdr.org) - Primary reference for SDR concepts and implementation
  • Online textbook providing foundational knowledge for software-defined radio programming
  • Essential resource for understanding DSP fundamentals and GNU Radio workflows

• Claude 4 Sonnet (Anthropic) via Warp.dev - Assisted with code refactoring, documentation improvements, and technical problem-solving
• Development Note: Most of the application was created without AI assistance in the previous year. Claude has been recently introduced to help clean up code, refactor existing functionality, and implement new features. The results are quite impressive imho.

• GNU Radio - Core signal processing framework
• gr-osmosdr - Hardware abstraction layer for SDR devices
• NumPy - Numerical processing and data manipulation
• Matplotlib - Spectrum visualization and plotting
• Bottle - Lightweight Python web framework
• Waitress - Lightweight Python HTTP server
• APScheduler - In-process job scheduling

• Alpine.js - Reactive web interface framework
• Bulma CSS - Modern CSS framework for UI styling
• Panzoom - Interactive image zoom functionality
• PhotoSwipe - Image gallery and lightbox with preloading
• iziToast - Notifications
• cRonstrue - Human-readable descriptions for cron expressions